Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning

1 code implementation • 19 May 2023 • Mustafa Safa Ozdayi, Charith Peris, Jack FitzGerald, Christophe Dupuy, Jimit Majmudar, Haidar Khan, Rahil Parikh, Rahul Gupta

We present a novel approach which uses prompt-tuning to control the extraction rates of memorized content in LLMs.

The Impact of Data Distribution on Fairness and Robustness in Federated Learning

1 code implementation • 29 Nov 2021 • Mustafa Safa Ozdayi, Murat Kantarcioglu

Particularly, as the data distributions of agents differ, the accuracy of the trained models drop.

Fairness Federated Learning

Fair Machine Learning under Limited Demographically Labeled Data

1 code implementation • 3 Jun 2021 • Mustafa Safa Ozdayi, Murat Kantarcioglu, Rishabh Iyer

In such a setting, we design fair training algorithms which exhibit both good utility, and low bias.

BIG-bench Machine Learning Bilevel Optimization +1

BlockFLA: Accountable Federated Learning via Hybrid Blockchain Architecture

no code implementations • 14 Oct 2020 • Harsh Bimal Desai, Mustafa Safa Ozdayi, Murat Kantarcioglu

It has been shown that an attacker can inject backdoors to the trained model during FL, and then can leverage the backdoor to make the model misclassify later.

Federated Learning

Improving Accuracy of Federated Learning in Non-IID Settings

no code implementations • 14 Oct 2020 • Mustafa Safa Ozdayi, Murat Kantarcioglu, Rishabh Iyer

Particularly, in settings where local data distributions vastly differ among agents, FL performs rather poorly with respect to the centralized training.

Federated Learning

Defending against Backdoors in Federated Learning with Robust Learning Rate

1 code implementation • 7 Jul 2020 • Mustafa Safa Ozdayi, Murat Kantarcioglu, Yulia R. Gel

In addition, we also provide convergence rate analysis for our proposed scheme.

Backdoor Attack Federated Learning +1